During the Pacific marine heatwave of 2014–2016, abundance and quality of several key forage fish species in the Gulf of Alaska were simultaneously reduced throughout the system. Capelin (Mallotus catervarius), sand lance (Ammodytes personatus), and herring (Clupea pallasii) populations were at historically low levels, and within this community abrupt declines in portfolio effects identify trophic instability at the onset of the heatwave. Although compensatory changes in age structure, size, growth or energy content of forage fish were observed to varying degrees among all these forage fish, none were able to fully mitigate adverse impacts of the heatwave, which likely included both top‐down and bottom‐up forcing. Notably, changes to the demographic structure of forage fish suggested size‐selective removals typical of top‐down regulation. At the same time, changes in zooplankton communities may have driven bottom‐up regulation as copepod community structure shifted toward smaller, warm water species, and euphausiid biomass was reduced owing to the loss of cold‐water species. Mediated by these impacts on the forage fish community, an unprecedented disruption of the normal pelagic food web was signaled by higher trophic level disruptions during 2015–2016, when seabirds, marine mammals, and groundfish experienced shifts in distribution, mass mortalities, and reproductive failures. Unlike decadal‐scale variability underlying ecosystem regime shifts, the heatwave appeared to temporarily overwhelm the ability of the forage fish community to buffer against changes imposed by warm water anomalies, thereby eliminating any ecological advantages that may have accrued from having a suite of coexisting forage species with differing life‐history compensations.

Sperm whales have depredated black cod (Anoplopoma fimbria) from demersal longlines in the Gulf of Alaska for decades, but the behavior has recently spread in intensity and geographic coverage. Over a three-year period 11 bioacoustic tags were attached to adult sperm whales off Southeast Alaska during both natural and depredation foraging conditions. Measurements of the animals' dive profiles and their acoustic behavior under both behavioral modes were examined for statistically significant differences. Two rough categories of depredation are identified: "deep" and "shallow." "Deep depredating" whales consistently surface within 500 m of a hauling fishing vessel, have maximum dive depths greater than 200 m, and display significantly different acoustic behavior than naturally foraging whales, with shorter inter-click intervals, occasional bouts of high "creak" rates, and fewer dives without creaks. "Shallow depredating" whales conduct dives that are much shorter, shallower, and more acoustically active than both the natural and deep depredating behaviors, with median creak rates three times that of natural levels. These results suggest that depredation efforts might be measured remotely with passive acoustic monitoring at close ranges.

Between 15 and 17 August 2010, a simple two-element vertical array was deployed off the continental slope of Southeast Alaska in 1200 m water depth. The array was attached to a vertical buoy line used to mark each end of a longline fishing set, at 300 m depth, close to the sound-speed minimum of the deep-water profile. The buoy line also served as a depredation decoy, attracting seven sperm whales to the area. One animal was tagged with both a LIMPET dive depth-transmitting satellite and bioacoustic "B-probe" tag. Both tag datasets were used as an independent check of various passive acoustic schemes for tracking the whale in depth and range, which exploited the elevation angles and relative arrival times of multiple ray paths recorded on the array. Analytical tracking formulas were viable up to 2 km range, but only numerical propagation models yielded accurate locations up to at least 35 km range at Beaufort sea state 3. Neither localization approach required knowledge of the local bottom bathymetry. The tracking system was successfully used to estimate the source level of an individual sperm whale's "clicks" and "creaks" and predict the maximum detection range of the signals as a function of sea state.

Folkert. Relationship between sperm whale (Physeter macrocephalus) click structure and size derived from videocamera images of a depredating whale (sperm whale prey acquisition). Journal of the Acoustical Society of America, Acoustical Society of America, 2009America, , pp.3444-3453. 10.1121 Relationship between sperm whale (Physeter macrocephalus) click structure and size derived from videocamera images of a depredating whale (sperm whale prey acquisition) Sperm whales have learned to depredate black cod ͑Anoplopoma fimbria͒ from longline deployments in the Gulf of Alaska. On May 31, 2006, simultaneous acoustic and visual recordings were made of a depredation attempt by a sperm whale at 108 m depth. Because the whale was oriented perpendicularly to the camera as it contacted the longline at a known distance from the camera, the distance from the nose to the hinge of the jaw could be estimated. Allometric relationships obtained from whaling data and skeleton measurements could then be used to estimate both the spermaceti organ length and total length of the animal. An acoustic estimate of animal length was obtained by measuring the inter-pulse interval ͑IPI͒ of clicks detected from the animal and using empirical formulas to convert this interval into a length estimate. Two distinct IPIs were extracted from the clicks, one yielding a length estimate that matches the visually-derived length to within experimental error. However, acoustic estimates of spermaceti organ size, derived from standard sound production theories, are inconsistent with the visual estimates, and the derived size of the junk is smaller than that of the spermaceti organ, in contradiction with known anatomical relationships.

We present an ocean-basin-scale dataset that includes tail fluke photographic identification (photo-ID) and encounter data for most living individual humpback whales (Megaptera novaeangliae) in the North Pacific Ocean. The dataset was built through a broad collaboration combining 39 separate curated photo-ID catalogs, supplemented with community science data. Data from throughout the North Pacific were aggregated into 13 regions, including six breeding regions, six feeding regions, and one migratory corridor. All images were compared with minimal pre-processing using a recently developed image recognition algorithm based on machine learning through artificial intelligence; this system is capable of rapidly detecting matches between individuals with an estimated 97–99% accuracy. For the 2001–2021 study period, a total of 27,956 unique individuals were documented in 157,350 encounters. Each individual was encountered, on average, in 5.6 sampling periods (i.e., breeding and feeding seasons), with an annual average of 87% of whales encountered in more than one season. The combined dataset and image recognition tool represents a living and accessible resource for collaborative, basin-wide studies of a keystone marine mammal in a time of rapid ecological change.